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MonoPatchNeRF: Improving Neural Radiance Fields with Patch-based Monocular Guidance
Our experiments show 4x the performance of RegNeRF and 8x that of FreeNeRF on average F1@2cm for ETH3D MVS benchmark, suggesting a fruitful research direction to improve the geometric accuracy of NeRF-based models, and sheds light on a potential future approach to enable NeRF-based optimization to eventually outperform traditional MVS.
Region-Based Representations Revisited
We investigate whether region-based representations are effective for recognition.
Sparse SPN: Depth Completion from Sparse Keypoints
Our long term goal is to use image-based depth completion to quickly create 3D models from sparse point clouds, e. g. from SfM or SLAM.
QFF: Quantized Fourier Features for Neural Field Representations
Instead, we propose to encode features in bins of Fourier features that are commonly used for positional encoding.
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